Data Quality for AI

AI & Automation
The success of AI transformation depends on high-quality, consistent, and trustworthy data. Without it, incorrect outputs and hallucinations are a risk.

Key questions and insights

Why is data quality key to AI transformation?

AI needs trustworthy data, not just computing power.

What specific data issues most often complicate AI?

In practice, there are incomplete data, duplicates, incorrect codes, and different structures across systems and countries.

How can consistent data be ensured across systems and countries?

Data must be consistent to minimize the risk of incorrect results and hallucinations.

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This theme grew out of our Primetime conferences. Explore the upcoming events and the full programme.

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